Introduction

Physical function, which is the ability to perform both basic and instrumental activities of daily living, is increasingly recognized as integral to healthy aging. Physical function is related to hospitalization (1), long-term nursing home care (2, 3), and increased mortality (3, 4). With the proportion of the U.S. population age 65 years or older expected to more than double to 89 million people by 2050 (5), identifying modifiable factors that may help to prevent or delay physical function decline among older adults is of critical public health importance.

Prior research has found that women with a healthier diet, as measured by the Alternative Healthy Eating Index-2010 (AHEI), had a lower risk of developing impairments in physical function (6). However, it is unknown whether this association is consistent in men and prior studies have indicated significant sex differences in physical function patterns in older adults (7-9). Thus, we used data from 12,658 men from the Health Professionals Follow-Up Study to examine the association between diet quality and impairment in physical function.

Methods

The Health Professionals Follow-up Study (HPFS) began in January 1986 with the enrollment of 51,529 male dentists, veterinarians, pharmacists, optometrists, podiatrists, and osteopaths who were 40 years of age and older and living throughout the US. On the initial questionnaire, participants provided a medical history and information on lifestyle and risk factors potentially related to cancer, cardiovascular disease and other medical conditions. Follow-up questionnaires have been mailed every two years to update individual characteristics and to identify incident diagnoses. A food frequency questionnaire (FFQ) was included on the initial questionnaire and every four years thereafter. The 2008 and 2012 questionnaires included the Medical Outcomes Study Short Form-36 (SF-36), a 36-item questionnaire that evaluates eight health concepts, including physical functioning. The study was approved by the Institutional Review Boards of Brigham and Women’s Hospital and the Harvard T.H. Chan School of Public Health.

Diet Assessment

On the FFQ, participants reported their average frequency of food consumption during the previous year based on the units or portion sizes specified on the questionnaire. Frequency is reported using nine possible responses ranging from “never or less than once per month” to “6 or more times per day”. The FFQ has been validated in the HPFS men against 7-day diet records and good reproducibility of the dietary questionnaires has been documented (10, 11).

The AHEI criteria and methods for calculating the score have been previously described in detail (12). Briefly, the AHEI consists of 11 components: 6 components for which higher intakes are better (vegetables, fruit, whole grains, nuts and legumes, long-chain omega-3 fatty acids, and polyunsaturated fatty acids); 1 component for which moderate intake is better (alcohol: 3.5 or more drinks/day is assigned 0 points, nondrinkers are assigned 2.5 points, and 0.5–2.0 drinks/day is assigned 10 points); and 4 components for which lower intake is better (sugar-sweetened beverages and fruit juice, red and processed meats, trans fatty acids, and sodium). Each component is given a minimum score of zero for the worst level of intake and a maximum score of 10 for the best level, with intermediate values scored proportionally. The “best” levels of intake were determined a priori and based on a combination of the current dietary guidelines and the scientific literature regarding the dietary factor and chronic disease risk. All the component scores are summed to obtain the total AHEI scores, with a range from 0 (non-adherence) to 110 (perfect adherence).

Physical Function

Information on physical function was collected on the SF-36 questionnaire, a widely used and validated instrument (13). The physical function domain of the SF-36 is a consistent and reliable predictor of morbidity and mortality in a variety of populations (4, 14, 15). The physical function component of the SF-36 is comprised of 10 questions regarding physical limitations in performing the following activities: bathing/ dressing yourself, walking one block, walking several blocks, walking more than one mile, bending/kneeling, climbing one flight of stairs, climbing several flights of stairs, lifting groceries, moderate activities, and vigorous activities. Each question has the same three response choices; each answer of “Yes, limited a lot” is assigned one point, an answer of “Yes, limited a little” is assigned two points, and an answer of “No, not limited at all” is assigned three points. A raw score is derived from the set of 10 questions and ranges from a minimum of 10 points to a maximum of 30 points. The raw score is then transformed to a 100-point score, with a score of 100 considered highest physical function. A score of 80 or less has been established to represent clinically meaningful physical impairment (16); this cutoff point has been used in other epidemiologic studies (16, 17).

Statistical Analysis

To evaluate the association between AHEI and incident impairment in physical function, we calculated AHEI as the mean of the scores from the 2002, 2006 and 2010 FFQs to reduce measurement error and to represent longer-term diet. Incident physical impairment was assessed from 2008 to 2012; in 2008, we excluded men with a physical function score <80, and identified incident cases in 2012. Thus, for the study population, we excluded men who died before 2008 (n=18,820), did not respond to the physical function questions in 2008 (n=2,693) or 2012 (n=10,998), had physical function impairment in 2008 (n=5,884), or did not respond to at least two of the three FFQs (n=477), leaving a study population of 12,658 men.

We used logistic regression models to calculate the odds ratio and 95% confidence intervals for physical impairment across five categories of diet quality and per a 10-unit increase in the total AHEI score. The categories were constructed to be equally spaced and to include approximately equal percentages of the population. The basic model was adjusted for age (continuous) and total energy intake (continuous, mean of caloric intake in 2002, 2006 and 2010). The multivariable model included primary, a priori risk factors for physical impairment; to mirror the diet assessments, we averaged potential confounding factors from 2002 through 2010: BMI (continuous, mean of 5 assessments), physical activity (<18, 18–29, 30–41, 42–53, ≥ 54 MET-h/week, mean of 3 assessments) smoking status in 2010 (never, past, current), pack-years of smoking as of 2010 (zero, <10, 10–19, 20–29, ≥ 30, 5% missing), Geriatric Depression score (18) in 2008 (0, 1, 2–4, 5–15), and history of diagnoses (yes/no) of cancer, myocardial infarction, stroke, diabetes, hypertension, and high cholesterol as of 2010.

We also examined associations between the individual AHEI components and physical impairment using the same basic and multivariable models, plus an additional model further adjusted for the other components (the total AHEI score minus the score from the component of interest). Odds ratios were calculated within five a priori categories (0–1.9, 2–3.9, 4–5.9, 6–7.9, 8–10 points) and per a 2-point increase in the AHEI component score. This analysis was not conducted for the trans fatty acid component because all of the men had scores within the top two categories.

We also conducted analyses in which we investigated associations between the top 5 contributors to the food component groups based on caloric intake in the study population: vegetables, fruit, nuts and legumes, red and processed meats, and sugar-sweetened beverages and fruit juice. The foods were categorized into servings of never or < 1/month, 1–3/month, 1/week, 2–4/week, and ≥5/week. These are the response categories provided on the FFQ, with the top categories collapsed into one category due to small numbers. Tests for trend across AHEI score categories and score components were calculated by treating the categories as an ordinal variable in the logistic regression models and assigning the median value for that category.

Table 1 Age-standardized characteristicsa in 2008 of the study populationb, according to quintiles of the Alternative Health Eating Index score
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In additional analyses to test the robustness of the cutoff for physical function impairment, we tested alternative cutoffs for impairment (75, 70, and 65). Lastly, we conducted analyses to examine effect modification by age, BMI, and physical activity. All analyses were performed in SAS 9.3 (SAS Institute Inc., Cary, NC). All statistical tests were two sided and P < 0.05 was considered statistically significant.

Result

Characteristics of the study population in 2008 according to categories of the total AHEI score are shown in Table 1. Men with the highest AHEI scores, indicating a healthier diet pattern, tended to have a lower BMI, report higher levels of physical activity, and a lower prevalence of hypertension compared to men with lower AHEI scores.

The total AHEI score was strongly and linearly associated with decreased odds of physical impairment after adjusting for age and energy intake (Ptrend < 0.001), and this association remained significant after controlling for all covariates (Table 2). In the multivariable model, each 10-point increase in the total AHEI score was associated with 10% lower odds of physical impairment (OR=0.90, 95% CI 0.86–0.95), and in the categorical analysis, comparing extreme categories, men with AHEI scores ≥ 72 (the highest group) had a 26% lower likelihood (OR=0.74, 95% CI 0.63–0.86) compared with men in the lowest group (AHEI scores < 54).

For the AHEI components, after controlling for potential confounding factors, relations were all fairly modest, and few individual components had significant relations with risk of physical function impairment (Table 2). Overall, when we considered each component score as a continuous variable (ranging from 0–10), we found no relation of consumption of fruit, alcohol, whole grains, omega-3 fatty acids, or sodium with onset of physical function impairment. Each 2-point increase in score (representing an increasingly healthy intake of each component) was associated with significantly lower odds of physical impairment for vegetables (OR=0.94, 95% CI 0.90–0.99), nuts and legumes (OR=0.93, 95% CI 0.90–0.97), red and processed meats (OR=0.96, 95% CI 0.92–0.99), sugarsweetened beverages and fruit juice (OR=0.96, 95% CI 0.93–0.99), and polyunsaturated fatty acids (OR=0.91, 95% CI=0.86–0.97). With additional adjustment for the other component scores, the results for vegetables and for red and processed meats were further attenuated and the associations were no longer significant. For the extreme comparisons of “best” versus “worst” intake of nuts and legumes, sugar-sweetened beverages/fruit juice, and polyunsaturated fatty acids (those components that maintained significant linear associations, the odds ratio associated with a component score of 8–10 compared to a component score of 0–1.9, was 0.94 (95% CI 0.77–1.15) for nuts and legumes, 0.80 (95% CI 0.67–0.96) for sugar-sweetened beverages and fruit juice, and 0.79 (95% CI 0.64–0.97) for polyunsaturated fatty acids.

Table 2 Odds ratios (95% confidence intervals) of physical function impairment in 2012, as measured by the Physical Function scale of SF-36, within categories and per unit increase in the total and component AHEI scores among HPFS men
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Table 3 Multivariable odds ratiosa (95% confidence intervals) of physical function impairment in 2012, as measured by the Physical Function scale of SF-36, by consumption of the top food contributors to the AHEI food components in HPFS men
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Associations between the top food contributors to each foodbased AHEI component and physical impairment are shown in Table 3. In these analyses, we considered absolute intake categories rather than devising a score representing better and worse levels of intake. Higher consumption of lettuce (OR=0.76, 95% CI=0.62–0.92 comparing top versus bottom category of intake, Ptrend =0.007), broccoli (OR=0.71, 95% CI 0.49–1.05, Ptrend =0.02), blueberries (OR=0.82, 95% CI 0.70– 0.95, Ptrend =0.005), peanuts (OR=0.82, 95% CI 0.65–1.04, Ptrend =0.02), walnuts (OR=0.80, 95% CI 0.68–0.94, Ptrend =0.01) and other nuts (OR=0.76, 95% CI 0.61–0.96, Ptrend =0.003) were associated with lower odds of impairment. In contrast, higher intakes of hamburger (OR=1.25, 95% CI 1.03–1.51, Ptrend =0.006), bacon (OR=1.17, 95% CI 0.99–1.39, Ptrend =0.03), and sugar-sweetened carbonated beverages (OR=1.23, 95% CI 0.99–1.53, Ptrend =0.03) were associated with higher odds of physical function impairment.

In additional analyses, we tested definitions of physical impairment that were stricter than the ≤ 80 physical function score used to define impairment in our primary analysis; results remained very similar. Using a physical function score of ≤ 70, the OR per 10-point increase in total AHEI score was 0.88 (95% CI 0.84–0.92), and using a score of ≤ 60, the OR was 0.92 (95% CI 0.87–0.96). We also examined total AHEI and physical impairment within strata of age (≤ 75 and ≥ 75 years), BMI (≤ 25 and ≥ 25 kg/m2) and physical activity (≤ 35 and ≥ 35 MET-hours/week) and found significant inverse associations in all six strata (data not shown).

Discussion

In this large, cohort study, a healthier diet pattern was associated with approximately a 25% lower likelihood of developing impairment in physical function with aging. Overall, the AHEI diet pattern appeared more strongly associated with physical function than the individual components or individual foods, although greater intake of vegetables, nuts and legumes, and polyunsaturated fats, and lower intake of red/processed meats, and sugar-sweetened beverages was associated with modestly lower odds of physical function impairment. Similarly, when we considered specific foods, greater intakes of lettuce, broccoli, peanuts, walnuts and other nuts were associated with reduced odds of physical function impairment.

Our results are consistent with prior studies supporting an association between diet quality and physical function. This association has been observed across a range of dietary patterns including the Mediterranean diet (19-21), Diet Quality Index Revised (22), Prudent Diet Score (23), and the Healthy Eating Index (24) and across different self-reported (19, 23, 25) and in-person assessments (20, 22, 26, 27) of physical function. However, much of this prior work has been limited by crosssectional study designs, with only one measure of physical function; thus it cannot be determined whether better diet leads to better physical function or the reverse. Our prospective design was a major strength of the current study, including exclusion at baseline of men with poor physical function, thus minimizing the likelihood of reverse causation bias.

When we investigated the individual components of the AHEI score in relation to physical function, we found that greater intake of vegetables, nuts and legumes, and polyunsaturated fats were associated with modestly lower odds of physical function impairment. This finding is also consistent with prior work that has found increased vegetable (26, 28, 29) and nut/legume (6) intake to be association with better physical function. There are clear biological rationales for these findings. First, dietary patterns characterized by higher intakes of fruit, vegetables, legumes, fish, poultry and whole grains are inversely associated with plasma concentrations of inflammation markers (30). Secondly, antioxidants found in fruits and vegetables may reduce the accumulation of oxidative damage, and therefore decrease the risk of oxidative-related chronic diseases, such as cardiovascular disease, cancer, and neurodegenerative diseases (31, 32). Additionally, increased nut intake is associated with a reduction in the incidence of cardiovascular disease (33). Inflammation, oxidative stress and related chronic diseases are all strongly related to physical function (28, 34, 35), supporting the findings observed in this study.

Our study had numerous strengths including the multiple measures of diet and physical function, the ability to control for multiple potential confounders, and the large sample size. Potential limitations also need to be considered. Residual confounding cannot be ruled out in an observational study, and thus results should be interpreted with caution. However, associations between diet quality and physical function remained strong and significant after adjustment for a wide array of health and lifestyle factors. Also, there is potential for measurement error in both the dietary assessment and the outcome measurement. However, both assessment instruments are validated, and averages of diet were used to reduce measurement error of the exposure. Additionally, dietary intake was collected prospectively, and thus any misreporting of diet is expected to be random and would result in bias toward the null, suggesting that our results may underestimate true associations. Additionally, the SF-36 has been found to correlate well with in-person physical performance measures such as grip strength, longer timed-up-and-go, chair rises, three-minute walk test, and the six-minute walk test (36-38).

In summary, we found that better diet quality as measured by the AHEI was associated with lower odds of incident physical function impairment among older men. We also identified several food groups and foods associated with better physical function, such as vegetables (e.g., lettuce, broccoli) and nuts and legumes (e.g., peanuts, walnuts and other nuts). Given the value of physical function to health and quality of life, this may represent a particularly compelling public health rationale for improved focus on a healthy diet with aging.

Acknowledgements: This work was supported by grants from the National Institute of Health (UM1 CA167552 and T32 HL098048), and the California Walnuts Commission.

Conflict of interest: Dr. Grodstein has received unrestricted research awards from the California Walnut Commission and Nestle Waters LLC. Dr. Hagan reports no conflicts of interest.

Ethical standards: The study was approved by the Institutional Review Boards of Brigham and Women’s Hospital and the Harvard T.H. Chan School of Public Health.